Machine Learning Engineer

Healthcare systems around the world are collapsing, pandemic-induced burnout and staffing shortages have resulted in 1 in 4 clinicians wanting to leave the workforce, with a projected shortfall of 18 million practitioners expected by 2030. This situation has led to a significant decline in the quality of the doctor-patient relationships

Nabla's primary mission is to repair this relationship by building AI technology that will give physicians their most valuable resource back: their time.

To that end, we are building Nabla Copilot whose goal is to automate administrative tasks so that clinicians can focus on their patients and the quality of care.

Nabla has raised €17M in funding in Series A. Its HQ is based in the heart of Paris.

As a Machine Learning Engineer, you will leverage the latest advances in machine learning to build the "Copilot" of healthcare. To let our medical team focus on actual care, you will automate and help them with their most time-consuming tasks:

• filling out medical records
• summarizing consultations
• finding the right specialist for a given patient
• searching for medical information
• organizing schedules
• following-up with patients
• and much more!

You’ll be deeply involved in the ML roadmap, from definition to delivery. Within a team of experts who built large-scale production systems at Facebook, Apple, Google or Microsoft, you will:

• propose experiments, model architectures & data labeling strategies
• implement them and train models
• roll them out on our platform by working closely with product teams
• measure their performance in the real world to improve them over time

This position is full-time and based in Paris. Prefer to work remotely? Let's discuss!

Your DNA

• You have a strong machine learning background
• Designing, implementing, training and testing neural network architectures has no secret for you
• You can deploy models in real products & on various platforms (server, mobile, etc)
• You’re passionate about applying cutting-edge research in the real world
• You don’t use a deep neural net if a logistic regression will do
• Data preprocessing & labeling is your true and only passion
• You get your news from arXiv
• You do your shopping on Hugging Face
• You heat your home with GPUs (or just use Colab)